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Modeling Molecular Regulatory Networks with JigCell and PET

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Systems Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 500))

Summary

We demonstrate how to model macromolecular regulatory networks with JigCell and the Parameter Estimation Toolkit (PET). These software tools are designed specifically to support the process typically used by systems biologists to model complex regulatory circuits. A detailed example illustrates how a model of the cell cycle in frog eggs is created and then refined through comparison of simulation output with experimental data. We show how parameter estimation tools automatically generate rate constants that fit a model to experimental data.

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References

  1. G. Marlovits, C.J. Tyson, B. Novak, and J.J. Tyson.(1998) Modeling M-phase control in xenopus oocyte extracts: the surveillance mechanism for unreplicated DNA. Biophys. Chem. 72,169–184.

    Article  PubMed  CAS  Google Scholar 

  2. K.C. Chen, L. Calzone, A. Csikasz-Nagy, F.R. Cross, B.Novak, and J.J.Tyson.(2004) Integrative analysis of cell cycle control in budding yeast. Mol. Biol. Cell 15, 3841–3862.

    Article  PubMed  CAS  Google Scholar 

  3. A.C. Hindmarsh. (1983) ODEPACK: a systematized collection of ODE solvers, in Scientific Computing, ed. by R.S. Stepleman, North Holland Publishing Company, Amsterdam 55–64.

    Google Scholar 

  4. P. Mendes.(1997) Biochemistry by numbers: Simulation of biochemical pathways with Gepasi 3.Trends Biochem. Sci. 22, 361–363.

    Article  PubMed  CAS  Google Scholar 

  5. N.A. Allen, L. Calzone, K.C. Chen, A. Ciliberto, N. Ramakrishnan, C.A. Shaffer, J.C. Sible, J.J. Tyson, M.T. Vass, L.T. Watson, and J.W. Zwolak.(2003) Modeling regulatory networks at Virginia Tech. OMICS7, 285–299.

    Article  PubMed  CAS  Google Scholar 

  6. H. Sauro, M. Hucka, A. Finney, C. Wellock, H. Bolouri, J. Doyle, and H. Kitano. (2003) Next generation simulation tools: The Systems Biology Workbench and BioSPICE integration. OMICS7, 355–372.

    Article  PubMed  CAS  Google Scholar 

  7. J. Schaff, B. Slepchenko, Y. Choi, J. Wagner, D. Resasco, and L. Loew. (2001) Analysis of non-linear dynamics on arbitrary geometries with the Virtual Cell. Chaos 11, 115–131.

    Article  PubMed  CAS  Google Scholar 

  8. Y. Cao, H. Li, and L. Petzold.(2004) Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. J. Chem. Phys. 121, 4059–4067.

    Article  PubMed  CAS  Google Scholar 

  9. M. Gibson, and J. Bruck.(2000) Efficient exact stochastic simulation of chemical systems with many species and many channels. J. Phys. Chem. A 104, 1876–1889.

    Article  CAS  Google Scholar 

  10. D. Gillespie. (2001) Approximate accelerated stochastic simulation of chemically reacting systems. J. Chem. Phys. 115, 1716–1733.

    Article  CAS  Google Scholar 

  11. M. Vass, C. Shaffer, N. Ramakrishnan, L. Watson, and J. Tyson.(2006) The JigCell Model Builder: a spreadsheet interface for creating biochemical reaction network models.IEEE/ACM Trans. Computat. Biol. Bioinform. 3, 155–164.

    Article  CAS  Google Scholar 

  12. N. Allen, R. Randhawa, M. Vass, J.W. Zwolak, J.J. Tyson, L.T. Watson, and C. Shaffer. (2007) JigCell, http://jigcell.biol.vt.edu/.

  13. M. Vass, N. Allen, C. Shaffer, N. Ramakrishnan, L. Watson, and J. Tyson.(2004) The JigCell Model Builder and Run Manager. Bioinformatics 20, 3680–3681.

    Article  PubMed  CAS  Google Scholar 

  14. J.W. Zwolak, T. Panning, and R. Singhania. (2007) PET: parameter Estimation Toolkit, http://mpf.biol.vt.edu/pet.

  15. M. Hucka, A. Finney, H. Sauro, and 40 additional authors (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531.

    Article  PubMed  CAS  Google Scholar 

  16. M. Hucka, A. Finney, B.J. Bornstein, S.M. Keating, B.E. Shapiro, J. Matthews, B.L. Kovitz, M.J. Schilstra, A. Funahashi, J.C. Doyle, and H. Kitano.(2004) Evolving a lingua franca and associated software infrastructure for computational systems biology: the systems biology markup language (SBML) project. Syst. Biol. 1, 41–53.

    Article  CAS  Google Scholar 

  17. H. Sauro, and B. Ingalls.(2004) Conservation analysis in biochemical networks: computational issues for software writers. Biophys. Chem. 109, 1–15.

    Article  PubMed  CAS  Google Scholar 

  18. B. Ermentrout. (2002) Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students, SIAM.

    Google Scholar 

  19. StochKit. (2005) Project website, http://www.cs.ucsb.edu/cse/StochKit.

  20. E. Conrad. (2007) Oscill8, http://oscill8.sourceforge.net/.

  21. J. Zwolak, P. Boggs, and L. Watson (to appear) Odrpack95: A weighted orthogonal distance regression code with bound constraints. ACM Trans. Math. Softw.

    Google Scholar 

  22. P.T. Boggs, J.R. Donaldson, R.H. Byrd, and R.B. Schnabel.(1989) Algorithm 676: Odrpack: software for weighted orthogonal distance regression. ACM Trans. Math. Soft. 15, 348–364.

    Article  Google Scholar 

  23. D. Jones, C. Perttunen, and B. Stuckman.(1993) Lipschitzian optimization without the Lipschitz constant. J. Optim. Theory. Appl. 79, 157–181.

    Article  Google Scholar 

  24. P.T. Boggs, R.H. Byrd, and R.B. Schnabel.(1987) A stable and efficient algorithm for nonlinear orthogonal distance regression. SIAM J. Sci. Stat. Comput. 8, 1052–1078.

    Article  Google Scholar 

  25. J.W. Zwolak, J.J. Tyson, and L.T. Watson.(2005) Parameter estimation for a mathematical model of the cell cycle in frog eggs. J. Comp. Biol. 12, 48–63.

    Article  CAS  Google Scholar 

  26. J.W. Zwolak, J.J. Tyson, and L.T. Watson.(2005) Globally optimized parameters for a model of mitotic control in frog egg extracts.IEE Syst. Biol. 152, 81–92.

    Article  CAS  Google Scholar 

  27. A. Kumagai, and W.G. Dunphy.(1992) Regulation of the cdc25 protein during the cell cycle in xenopus extracts. Cell 70, 139–151.

    Article  PubMed  CAS  Google Scholar 

  28. A. Kumagai, and W.G. Dunphy.(1995) Control of the cdc2/cyclin B complex in Xenopus egg extracts arrested at a G2/M checkpoint with DNA synthesis inhibitors. Mol. Biol. Cell 6, 199–213.

    PubMed  CAS  Google Scholar 

  29. Z. Tang, T.R. Coleman, and W.G. Dunphy.(1993) Two distinct mechanisms for negative regulation of the wee1 protein kinase. EMBO J. 12, 3427–3436.

    PubMed  CAS  Google Scholar 

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Correspondence to Clifford A. Shaffer .

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© 2009 Humana Press

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Shaffer, C.A., Zwolak, J.W., Randhawa, R., Tyson, J.J. (2009). Modeling Molecular Regulatory Networks with JigCell and PET. In: Maly, I. (eds) Systems Biology. Methods in Molecular Biology, vol 500. Humana Press. https://doi.org/10.1007/978-1-59745-525-1_4

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  • DOI: https://doi.org/10.1007/978-1-59745-525-1_4

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-934115-64-0

  • Online ISBN: 978-1-59745-525-1

  • eBook Packages: Springer Protocols

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